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Results: 12
Number of items: 12
  • Open Access
    Zaghen, O., Eijkelboom, F., Pouplin, A., Liu, C., Welling, M., van de Meent, J.-W., & Bekkers, E. J. (2026). Riemannian Variational Flow Matching for Material and Protein Design. Paper presented at 14th International Conference on Learning Representations, Rio de Janeiro, Brazil. https://doi.org/10.48550/arXiv.2502.12981
  • Open Access
    Zimmermann, H. (2025). Variational inference for probabilistic programs and generative models. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Eijkelboom, F., Bartosh, G., Naesseth, C. A., Welling, M., & van de Meent, J.-W. (2025). Variational Flow Matching for Graph Generation. In A. Globerson, L. Mackey, D. Belgrave, A. Fan, U. Paquet, J. Tomczak, & C. Zhang (Eds.), 38th Conference on Neural Information Processing Systems (NeurIPS 2024): 10-15 December 2024, Vancouver, Canada (pp. 11735-11764). (Advances in Neural Information Processing Systems; Vol. 37). Neural Information Processing Systems Foundation. https://doi.org/10.52202/079017-0374
  • Open Access
    Zimmermann, H., Naesseth, C. A., & van de Meent, J.-W. (2025). VISA: Variational Inference with Sequential Sample-Average Approximations. In A. Globerson, L. Mackey, D. Belgrave, A. Fan, U. Paquet, J. Tomczak, & C. Zhang (Eds.), 38th Conference on Neural Information Processing Systems (NeurIPS 2024): 10-15 December 2024, Vancouver, Canada (pp. 138789-138808). (Advances in Neural Information Processing Systems; Vol. 37). Neural Information Processing Systems Foundation. https://doi.org/10.52202/079017-4403
  • Open Access
    Dijkman, J., Dijkstra, M., van Roij, R., Welling, M., van de Meent, J.-W., & Ensing, B. (2025). Learning Neural Free-Energy Functionals with Pair-Correlation Matching. Physical Review Letters, 134(5), Article 056103. https://doi.org/10.1103/PhysRevLett.134.056103
  • Open Access
    Eijkelboom, F., Zimmermann, H., Vadgama, S., Bekkers, E. J., Welling, M., Naesseth, C. A., & van de Meent, J.-W. (2025). Controlled Generation with Equivariant Variational Flow Matching. Proceedings of Machine Learning Research, 267, 15066-15078. https://proceedings.mlr.press/v267/eijkelboom25a.html
  • Open Access
    McInerney, D. J., Dickinson, W., Flynn, L. C., Young, A. C., Young, G. S., van de Meent, J.-W., & Wallace, B. C. (2024). Towards Reducing Diagnostic Errors with Interpretable Risk Prediction. In K. Duh, H. Gomez, & S. Bethard (Eds.), The 2024 Conference of the North American Chapter of the Association for Computational Linguistics : proceedings of the conference: NAACL 2024 : June 16-21, 2024 (Vol. 1, pp. 7193-7210). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.naacl-long.399
  • Open Access
    Esmaeili, B. (2024). Learning useful representations with variational autoencoders. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Esmaeili, B., Walters, R., Zimmermann, H., & van de Meent, J.-W. (2023). Topological Obstructions and How to Avoid Them. In A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), 37th Conference on Neural Information Processing Systems (NeurIPS 2023): 10-16 December 2023, New Orleans, Louisana, USA (pp. 8865-8884). (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://doi.org/10.52202/075280-0388
  • Open Access
    Zimmermann, H., Lindsten, F., van de Meent, J.-W., & Naesseth, C. A. (2023). A Variational Perspective on Generative Flow Networks. Transactions on Machine Learning Research, 2023, Article 612. https://openreview.net/forum?id=AZ4GobeSLq
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